├── code
    └── shp_cut_raster02.py
└── data
    └── FalseColor.zip


/code/shp_cut_raster02.py:
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 1 | # _*_ coding: utf-8 _*_
 2 | __author__ = 'xbr'
 3 | __date__ = '2019/1/2 18:06'
 4 | 
 5 | import operator
 6 | from osgeo import gdal, gdal_array, osr
 7 | import shapefile
 8 | 
 9 | try:
10 |     import Image
11 |     import ImageDraw
12 | except:
13 |     from PIL import Image, ImageDraw
14 | 
15 | # 用于裁剪的栅格数据
16 | raster = r'D:\FalseColor.tif'
17 | # 用于裁剪的多边形shp文件
18 | shp = r'D:\hancock'
19 | # 裁剪后的栅格数据
20 | output = r'D:\clip'
21 | 
22 | 
23 | def image2Array(i):
24 |     """
25 |     将一个Python图像库的数组转换为一个gdal_array图片
26 |     """
27 |     a = gdal_array.numpy.fromstring(i.tobytes(), 'b')
28 |     a.shape = i.im.size[1], i.im.size[0]
29 |     return a
30 | 
31 | 
32 | def world2Pixel(geoMatrix, x, y):
33 |     """
34 |     使用GDAL库的geomatrix对象((gdal.GetGeoTransform()))计算地理坐标的像素位置
35 |     """
36 |     ulx = geoMatrix[0]
37 |     uly = geoMatrix[3]
38 |     xDist = geoMatrix[1]
39 |     yDist = geoMatrix[5]
40 |     rtnX = geoMatrix[2]
41 |     rtnY = geoMatrix[4]
42 |     pixel = int((x - ulx) / xDist)
43 |     line = int((uly - y) / abs(yDist))
44 |     return (pixel, line)
45 | 
46 | # 将数据源作为gdal_array载入
47 | srcArray = gdal_array.LoadFile(raster)
48 | # 同时载入gdal库的图片从而获取geotransform
49 | srcImage = gdal.Open(raster)
50 | geoTrans = srcImage.GetGeoTransform()
51 | # 使用PyShp库打开shp文件
52 | r = shapefile.Reader("{}.shp".format(shp))
53 | # 将图层扩展转换为图片像素坐标
54 | minX, minY, maxX, maxY = r.bbox
55 | ulX, ulY = world2Pixel(geoTrans, minX, maxY)
56 | lrX, lrY = world2Pixel(geoTrans, maxX, minY)
57 | # 计算新图片的尺寸
58 | pxWidth = int(lrX - ulX)
59 | pxHeight = int(lrY - ulY)
60 | clip = srcArray[:, ulY:lrY, ulX:lrX]
61 | # 为图片创建一个新的geomatrix对象以便附加地理参照数据
62 | geoTrans = list(geoTrans)
63 | geoTrans[0] = minX
64 | geoTrans[3] = maxY
65 | # 在一个空白的8字节黑白掩膜图片上把点映射为像元绘制市县
66 | # 边界线
67 | pixels = []
68 | for p in r.shape(0).points:
69 |     pixels.append(world2Pixel(geoTrans, p[0], p[1]))
70 | rasterPoly = Image.new("L", (pxWidth, pxHeight), 1)
71 | # 使用PIL创建一个空白图片用于绘制多边形
72 | rasterize = ImageDraw.Draw(rasterPoly)
73 | rasterize.polygon(pixels, 0)
74 | # 使用PIL图片转换为Numpy掩膜数组
75 | mask = image2Array(rasterPoly)
76 | # 根据掩膜图层对图像进行裁剪
77 | clip = gdal_array.numpy.choose(mask, (clip, 0)).astype(gdal_array.numpy.uint8)
78 | print clip.max()
79 | # 将NDVI保存为tiff文件
80 | gdal_array.SaveArray(clip, "{}.tif".format(output),
81 |                      format="GTiff", prototype=raster)
82 | 


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/data/FalseColor.zip:
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https://raw.githubusercontent.com/xbr2017/PyGdal_vector_clip_raster/e5e95a9bec6439875e15cbfd5afb146fd5abcd70/data/FalseColor.zip


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